A combined static output feedback-PID control for TITO process based particle swarm optimization: simulation and practical implementation for the poultry house system

This paper presents a novel method for designing and implementing static output feedback (SOF) combined with a proportional, integral, derivative (PID) controller tuned by the multidimensional Particle Swarm Optimization (PSO) algorithm in a broiler house prototype. The poultry house system is shown to be challenging for controlling due to the strong interaction between the main inputs (heating and ventilation actuators), and outputs (temperature and humidity) of the system. For this purpose, an on-line collection data was developed in the model to obtain the Multi-variable state-space model. Based on the SOF technique, the two-input two-output (TITO) poultry house model is decomposed into two single loops. Then, the equivalent transfer function (ETF) of each loop is controlled by applying a PID controller based multidimensional Particle Swarm Optimization tuning. Moreover, to show the effectiveness of this proposed strategy (SOF-PID), numerical simulations and experimental validation have been conducted for a poultry house prototype. Simulations results have validated the effectiveness of the proposed controller in the system with a comparison with those of Ant Colony Optimization, Genetic Algorithm, and Ziegler Nichols approaches.